In this paper it is argued that occupational and organizational codes maximize the correspondence between activities and easily observable characteristics at the time of their development. Over time the codes become less relevant, leading to the false impression that the segregation of...

This paper concerns estimating parameters in a high-dimensional dynamic factor

We review the past 25 years of time series research that has been published in journals managed by the International Institute of Forecasters (<I>Journal of Forecasting </I>1982-1985; <I>International Journal of Forecasting </I>1985-2005). During this period, over one third of all papers published in these...</i></i>

A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of...

This paper introduces the Werden-Froeb Index (WFI) to assist in evaluating merger-specific efficiencies in horizontal mergers. The index measures the weighted average reduction in marginal costs required to restore pre-merger equilibrium prices and quantities after the (full or partial) merger...

We present new results for the likelihood-based analysis of the dynamic factor model that possibly includes intercepts and explanatory variables. The latent factors are modelled by stochastic processes. The idiosyncratic disturbances are specified as autoregressive processes with mutually...

An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log-density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian...

The linear Gaussian state space model for which the common variance is treated as a stochastic time-varying variable is considered for the modelling of economic time series. The focus of this paper is on the simultaneous estimation of parameters related to the stochastic processes of the mean...

We combine micro and macro unemployment duration data to study the effects of the business cycle on the outflow from unemployment. We allow the cycle to affect individual exit probabilities of unemployed workers as well as the composition of the total inflow into unemployment. We estimate the...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...